3 papers
math.ST2026
Exploiting Exact Conditionals Improves Conditioning: Provably Fast Mixing Time Bounds By Sampling from the Marginal
Abhijit Chowdhary, Federica Milinanni, Julianne Chung +1
The problem of sampling from a probability distribution arises in many applications such as posterior sampling in hierarchical Bayesian inverse problems and Gaussian processes for…
math.NA2024
Efficient hyperparameter estimation in Bayesian inverse problems using sample average approximation
Julianne Chung, Scot M. Miller, Malena Sabate Landman +1
In Bayesian inverse problems, it is common to consider several hyperparameters that define the prior and the noise model that must be estimated from the data. In particular, we are…
math.NA2024
Inexact Generalized Golub-Kahan Methods for Large-Scale Bayesian Inverse Problems
Yutong Bu, Julianne Chung
Solving large-scale Bayesian inverse problems presents significant challenges, particularly when the exact (discretized) forward operator is unavailable. These challenges often ari…